CN111817994A - Modulation identification method and device based on phase difference constellation diagram clustering - Google Patents

Modulation identification method and device based on phase difference constellation diagram clustering Download PDF

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CN111817994A
CN111817994A CN202010727281.6A CN202010727281A CN111817994A CN 111817994 A CN111817994 A CN 111817994A CN 202010727281 A CN202010727281 A CN 202010727281A CN 111817994 A CN111817994 A CN 111817994A
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phase difference
symbol rate
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王亚昕
边东明
唐璟宇
胡婧
朱宏鹏
万扬洋
田世伟
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Army Engineering University of PLA
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Abstract

The invention discloses a modulation identification method and a device based on phase difference constellation diagram clustering, wherein the method comprises the following steps: carrying out symbol rate estimation, matched filtering, timing error estimation and difference filtering on a received signal to obtain a corresponding complex baseband signal, carrying out adjacent sampling point subtraction on the complex baseband signal to realize phase difference, carrying out clustering feature extraction on a constellation diagram corresponding to sampling points after the phase difference, and carrying out identification of signal modulation according to the result of the clustering feature extraction. The invention can reduce the algorithm complexity, is suitable for various modulations, does not need to receive signals for accurate synchronization and has high identification accuracy.

Description

Modulation identification method and device based on phase difference constellation diagram clustering
Technical Field
The invention relates to the technical field of satellite communication and digital signal processing, in particular to a modulation identification method and device based on phase difference constellation diagram clustering.
Background
In the field of uncooperative satellite communication, the parameters and channels of signals are unknown, and in an uncooperative satellite communication system, the modulation parameters of the signals need to be estimated blindly from the obtained signals, so that blind demodulation of the signals is realized. Therefore, the research on modulation identification is of great significance in a non-cooperative satellite communication system.
In the documents on modulation identification published at home and abroad at present, the identification method can be roughly divided into: a modulation recognition method based on likelihood (LBlikelihood-based) and a modulation recognition method based on feature (FB feature-based). Modulation identification based on likelihood methods can be seen as a multiple hypothesis testing problem. The following are commonly used: average likelihood ratio test method, generalized likelihood ratio test method, and mixed likelihood ratio test method. The feature-based modulation identification method focuses on the selection of feature parameters and decision criteria. The common characteristic parameters are instantaneous statistical characteristics, frequency domain characteristics, wavelet domain characteristics, high-order cumulant, cyclic cumulant and the like; common decision criteria are threshold decision, support vector machine, neural network, etc.
The foregoing modulation identification methods have some disadvantages: 1. the identification types are limited; 2. requiring synchronization of the received signal; 3. the recognition accuracy is not high.
Disclosure of Invention
The embodiment of the invention provides a modulation identification method and device based on phase difference constellation diagram clustering, which can reduce algorithm complexity, are suitable for various modulations, do not need to receive signals for accurate synchronization and have high identification accuracy.
The first aspect of the embodiments of the present invention provides a modulation identification method based on phase difference constellation diagram clustering, which may include:
carrying out symbol rate estimation, matched filtering, timing error estimation and difference filtering on a received signal to obtain a corresponding complex baseband signal;
performing adjacent sampling point subtraction on the complex baseband signal to realize phase difference;
performing clustering feature extraction on the constellation diagram corresponding to the sampling points after the phase difference;
and identifying signal modulation according to the result of the cluster feature extraction.
Further, the above-mentioned performing symbol rate estimation, matched filtering, timing error estimation and difference filtering on the received signal to obtain a corresponding complex baseband signal includes:
carrying out FFT calculation on the envelope of the received signal to obtain an envelope spectrum, and estimating a symbol rate based on a peak value in the envelope spectrum;
performing matched filtering on the received signal to obtain a maximum output signal-to-noise ratio signal;
estimating a timing error of a received signal by adopting an average estimation algorithm of non-data-assisted NDA;
and carrying out interpolation operation on the estimated timing error and the non-optimal sampling point obtained by sampling based on a cubic interpolation filter.
Further, the performing FFT computation on the envelope of the received signal to obtain an envelope spectrum, and estimating a symbol rate based on a peak in the envelope spectrum includes:
performing a modulus on the received signal by adopting an envelope spectrum estimation algorithm, and performing FFT operation on the baseband signal subjected to the modulus to obtain a corresponding envelope spectrum;
the position of the envelope spectrum at the spectral line is extracted to obtain a symbol rate estimate, wherein the envelope spectrum has a spectral line that is significant at the symbol rate.
Further, the method comprisesThe complex baseband signal is
Figure BDA0002600620500000021
Wherein the content of the first and second substances,
Figure BDA0002600620500000022
for modulating the phase, Δ ωcIs a normalized carrier frequency offset.
The absolute phases of the nth and n +1 th symbols are:
Figure BDA0002600620500000023
Figure BDA0002600620500000024
and is provided with
Figure BDA0002600620500000025
Furthermore, the constellation diagram state x which the received signal should have is recovered after the phase difference1Comprises the following steps: x is the number of1(m)＝x*(N) · x (N-1), wherein N ═ 2,3.. N, m ═ N-1.
A second aspect of the embodiments of the present invention provides a modulation identification apparatus based on phase difference constellation clustering, which may include:
the received signal processing module is used for carrying out symbol rate estimation, matched filtering, timing error estimation and difference filtering on the received signal to obtain a corresponding complex baseband signal;
the phase difference realization module is used for subtracting adjacent sampling points of the complex baseband signal to realize phase difference;
the clustering feature extraction module is used for extracting clustering features of the constellation diagram corresponding to the sampling points after the phase difference;
and the signal modulation identification module is used for identifying signal modulation according to the result of the cluster feature extraction.
Further, the received signal processing module includes:
a symbol rate estimation unit, configured to perform FFT computation on an envelope of a received signal to obtain an envelope spectrum, and estimate a symbol rate based on a peak in the envelope spectrum;
the matched filtering unit is used for performing matched filtering on the received signal to obtain a signal with the maximum output signal-to-noise ratio;
a timing error estimation unit for estimating the timing error of the received signal by using an average estimation algorithm of non-data-aided NDA;
and the difference filtering unit is used for carrying out interpolation operation on the estimated timing error and the non-optimal sampling point obtained by sampling based on the cubic interpolation filter.
Further, the symbol rate estimation unit includes:
the envelope spectrum calculating subunit is used for performing modulo calculation on the received signal by adopting an envelope spectrum estimation algorithm, and then performing FFT operation on the baseband signal subjected to the modulo calculation to obtain a corresponding envelope spectrum;
and the symbol rate estimation subunit is used for extracting the position of the envelope spectrum at the spectral line to obtain a symbol rate estimation value, wherein the envelope spectrum has an obvious spectral line at the symbol rate.
Further, the complex baseband signal is
Figure BDA0002600620500000031
Wherein the content of the first and second substances,
Figure BDA0002600620500000032
for modulating the phase, Δ ωcIs a normalized carrier frequency offset.
The absolute phases of the nth and n +1 th symbols are:
Figure BDA0002600620500000033
Figure BDA0002600620500000034
and is provided with
Figure BDA0002600620500000035
Furthermore, the constellation diagram state x which the received signal should have is recovered after the phase difference1Comprises the following steps: x is the number of1(m)＝x*(N) · x (N-1), wherein N ═ 2,3.. N, m ═ N-1. The invention has the beneficial effects that:
in the embodiment of the invention, modulation identification of the communication satellite is realized through symbol rate estimation, matched filtering, timing error estimation, interpolation filtering, phase difference, constellation feature extraction and classification, the algorithm complexity is reduced, and meanwhile, the algorithm is suitable for multiple modulations, does not need to receive signals, is accurate and synchronous and has high identification accuracy.
Specifically, the method is suitable for common modulation modes of satellite communication, such as BPSK, QPSK, 8PSK, OQPSK, 16QAM, 16APSK and 32 APSK. The method of the present invention allows for some frequency offset and timing error in the received signal. The method of the invention can achieve 100% identification accuracy under reasonable signal-to-noise ratio.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flowchart of a modulation identification method based on phase difference constellation clustering according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of another modulation identification method based on phase difference constellation clustering according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a modulation identification apparatus based on phase difference constellation clustering according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a received signal processing module according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a symbol rate estimation unit according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of another modulation identification apparatus based on phase difference constellation clustering according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "including" and "having" and any variations thereof in the description and claims of the invention and the above-described drawings are intended to cover a non-exclusive inclusion, and the terms "first" and "second" are intended to distinguish between different names and not necessarily to represent a sequential order in ranking. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
It should be noted that the flowchart of the method in the embodiment of the present invention may be a computer with data analysis processing capability.
As shown in fig. 1, the modulation identification method based on phase difference constellation clustering may at least include the following steps:
s101, carrying out symbol rate estimation, matched filtering, timing error estimation and difference filtering on the received signal to obtain a corresponding complex baseband signal.
In this application, the apparatus may perform symbol rate estimation, matched filtering, timing error estimation, and difference filtering on a received signal to obtain a corresponding complex baseband signal. In a specific implementation, each processing procedure for a received signal is executed in detail as follows:
for symbol rate estimation: the device can adopt an envelope spectrum estimation algorithm commonly used in engineering to perform modular operation on the baseband signal, then perform FFT operation to obtain an envelope spectrum, wherein the envelope spectrum has obvious spectral lines at a symbol rate, and a symbol rate estimation value is obtained by extracting the positions of the spectral lines.
For matched filtering: the device can carry out matched filtering on the received signal by arranging a matched filter at the receiving end to obtain the output signal with the maximum signal-to-noise ratio.
For timing error estimation: the device may assume that the received signal has a time duration LT, during which the timing error is assumed to be constant without change. If the pair adopts the sequence rkPerforming a squaring operation, including a frequency of 1/T in the samplesbThe spectral components of (2) can be extracted by calculating the fourier coefficients of each segment of data. It can be shown that,
Figure BDA0002600620500000051
is an unbiased estimate of the timing error. The timing error estimation equation is as follows:
Figure BDA0002600620500000052
filtering for the difference: the device can eliminate the influence of timing error by adopting a feedforward method, and utilizes the estimated timing error and the non-optimal sampling point obtained by sampling to carry out interpolation operation through an interpolation filter so as to approach the nearest sampling value. Interpolation filtering is used here. There are many forms of interpolation filters. A commonly used cubic interpolation filter is of the form:
y(t)＝b-2(u)x[(m+2)Ts]+b-1(u)x[(m+1)Ts]+b0(u)x[mTs]+b1(u)x[(m-1)Ts]
having a coefficient of
Figure BDA0002600620500000053
Wherein mu is a fractional interval parameter in the interpolation filter algorithm, and the timing error can be obtained by estimation
Figure BDA0002600620500000054
And (4) calculating.
μk＝((kTi+Tb)/Ts)mod1
mk＝INT[(kTi+Tb)/Ts]
It should be noted that, the complex baseband signal has frequency offset, and the influence of the frequency offset needs to be eliminated through phase difference.
And S102, performing adjacent sampling point subtraction on the complex baseband signal to realize phase difference.
In specific implementation, the device can perform adjacent sampling point subtraction on the complex baseband signal to realize phase difference, so that the influence of carrier frequency offset is eliminated.
For example, the complex baseband signal with frequency offset is
Figure BDA0002600620500000056
Wherein the content of the first and second substances,
Figure BDA0002600620500000055
for modulating the phase, Δ ωcIs a normalized carrier frequency offset.
The absolute phases of the nth and n +1 th symbols are:
Figure BDA0002600620500000061
Figure BDA0002600620500000062
and is provided with a plurality of groups of the materials,
Figure BDA0002600620500000063
in the phase-modulated signal, respectively
Figure BDA0002600620500000064
And
Figure BDA0002600620500000065
to carry modulation information. When the receiving end has carrier frequency deviation, the absolute phase of the current code element carries inherent modulation information and is more than that of the former code element by delta omegacTbReflected on the constellation diagram is the angle Δ ωcTbOver time, the rotation may cause the points on the signal constellation to assume a circular distribution, making subsequent identification impossible. In this case, the phase difference method is used to eliminate the interference of carrier frequency offset on the constellation diagram recovery. The difference equation is as follows:
x1(m)＝x*(n)·x(n-1)
n is 2,3.. N, m is N-1.
x1In order to recover the proper constellation diagram state of the signal, the signal is input into the signal modulation identification module to complete the identification of the signal modulation.
And S103, extracting the clustering characteristics of the constellation diagram corresponding to the sampling points after the phase difference.
It can be understood that the device may obtain a corresponding constellation diagram by using the sampling points after the phase difference, then perform mean clustering on the constellation diagram, and extract the clustered features, where the clustered features at least include a clustering center point, a clustering position, and a clustering shape as a classification basis.
And S104, identifying signal modulation according to the result of the cluster feature extraction.
It should be noted that the mean clustering algorithm is sensitive to the clustering radius. Aiming at the coordinate position of a scattered point on a constellation diagram, the radius selection formula is as follows:
r＝(Vmax-Vmin)/cof
wherein Vmax is the maximum value of the in-phase component, Vmin is the minimum value of the in-phase component, cof chooses: the phase modulation signal is selected 10 and the amplitude modulation is selected 16.
And after the features are extracted, classifying according to the calculation result of the membership function. The membership function is:
Figure BDA0002600620500000066
wherein x is the number of the actual clustering central points, xthFor identifying the number of the clustering central points of each modulation theory in the set, snr is the measured signal-to-noise ratio, snrthIs the signal-to-noise threshold.
In the embodiment of the invention, modulation identification of the communication satellite is realized through symbol rate estimation, matched filtering, timing error estimation, interpolation filtering, phase difference, constellation feature extraction and classification, the algorithm complexity is reduced, and meanwhile, the algorithm is suitable for multiple modulations, does not need to receive signals, is accurate and synchronous and has high identification accuracy.
In a specific implementation manner of the present invention, the modulation identification process based on the phase difference constellation clustering may be as shown in fig. 2, and at least includes:
and S201, estimating the symbol rate.
And S202, matched filtering.
And S203, estimating a timing error.
And S204, filtering the difference value.
And S205, phase difference.
And S206, extracting and classifying the constellation characteristics.
It should be noted that, for a detailed description of the modulation identification process shown in fig. 2, reference may be made to the description in the foregoing method embodiment, and details are not described here again.
Aiming at the application scene of non-cooperative satellite communication, the diversity of modulation systems, the actual condition of received data and the requirement of identification accuracy rate are fully considered, and the method achieves the purpose of identifying various actual satellite communication signals with high accuracy rate by a phase difference constellation diagram clustering method.
The modulation identification apparatus based on phase difference constellation clustering according to the embodiment of the present invention will be described in detail with reference to fig. 3 to 5. It should be noted that, the modulation identification apparatus based on phase difference constellation clustering shown in fig. 3 is used for executing the method according to the embodiment shown in fig. 1 and fig. 2 of the present invention, for convenience of description, only the portion related to the embodiment of the present invention is shown, and details of the specific technology are not disclosed, please refer to the embodiment shown in fig. 1 and fig. 2 of the present invention.
Referring to fig. 3, a schematic structural diagram of a modulation identification apparatus based on phase difference constellation clustering is provided for an embodiment of the present invention. As shown in fig. 3, a modulation recognition apparatus 1 according to an embodiment of the present invention may include: the device comprises a received signal processing module 11, a phase difference implementation module 12, a clustering feature extraction module 13 and a signal modulation identification module 14. As shown in fig. 4, the received signal processing module 11 includes a symbol rate estimation unit 111, a matched filter unit 112, a timing error estimation unit 113, and a difference filter unit 114. The symbol rate estimation unit 111, as shown in fig. 5, includes an envelope spectrum calculation subunit 1111 and a symbol rate estimation subunit 1112.
And the received signal processing module 11 is configured to perform symbol rate estimation, matched filtering, timing error estimation, and difference filtering on the received signal to obtain a corresponding complex baseband signal.
In a specific implementation, the received signal processing module 11 includes:
and a symbol rate estimation unit 111, configured to perform FFT computation on the envelope of the received signal to obtain an envelope spectrum, and estimate a symbol rate based on a peak in the envelope spectrum.
In a specific implementation, the symbol rate estimation unit 111 includes:
and the envelope spectrum calculation subunit 1111 is configured to perform a modulo operation on the received signal by using an envelope spectrum estimation algorithm, and then perform an FFT operation on the modulo baseband signal to obtain a corresponding envelope spectrum.
A symbol rate estimation sub-unit 1112, configured to extract a position of the envelope spectrum at the spectral line to obtain a symbol rate estimation value, where the envelope spectrum has a spectral line that is significant at the symbol rate.
And a matched filtering unit 112, configured to perform matched filtering on the received signal to obtain a maximum output signal-to-noise ratio signal.
A timing error estimation unit 113, configured to estimate a timing error of the received signal by using an average estimation algorithm of non-data-aided NDA.
And a difference filtering unit 114, configured to perform interpolation operation on the estimated timing error and the sampled non-optimal sampling point based on a cubic interpolation filter.
And a phase difference implementation module 12, configured to perform subtraction on adjacent sampling points of the complex baseband signal to implement phase difference.
And the clustering feature extraction module 13 is configured to perform clustering feature extraction on the constellation diagram corresponding to the sampling points after the phase difference.
And the signal modulation identification module 14 is used for identifying signal modulation according to the result of the cluster feature extraction.
It should be noted that, for the detailed execution process in this embodiment, reference may be made to the detailed description in the above method embodiment, and details are not described here again.
In the embodiment of the invention, modulation identification of the communication satellite is realized through symbol rate estimation, matched filtering, timing error estimation, interpolation filtering, phase difference, constellation feature extraction and classification, the algorithm complexity is reduced, and meanwhile, the algorithm is suitable for multiple modulations, does not need to receive signals, is accurate and synchronous and has high identification accuracy.
An embodiment of the present invention further provides a computer storage medium, where the computer storage medium may store a plurality of instructions, where the instructions are suitable for being loaded by a processor and executing the method steps in the embodiments shown in fig. 1 and fig. 2, and a specific execution process may refer to specific descriptions of the embodiments shown in fig. 1 and fig. 2, which are not described herein again.
In addition, an embodiment of the present application further provides a modulation identification apparatus based on phase difference constellation clustering, where the apparatus may be a computer with data analysis processing capability, and as shown in fig. 6, the modulation identification apparatus 20 based on phase difference constellation clustering may include: the at least one processor 201, e.g., CPU, the at least one network interface 204, the user interface 203, the memory 205, the at least one communication bus 202, and optionally, a display 206. Wherein a communication bus 202 is used to enable the connection communication between these components. The user interface 203 may include a touch screen, a keyboard or a mouse, among others. The network interface 204 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), and a communication connection may be established with the server via the network interface 204. The memory 205 may be a high-speed RAM memory or a non-volatile memory (non-volatile memory), such as at least one disk memory, and the memory 205 includes a flash in the embodiment of the present invention. The memory 205 may optionally be at least one memory system located remotely from the processor 201. As shown in fig. 6, memory 205, which is a type of computer storage medium, may include an operating system, a network communication module, a user interface module, and program instructions.
It should be noted that the network interface 204 may be connected to a receiver, a transmitter, or other communication module, and the other communication module may include, but is not limited to, a WiFi module, a bluetooth module, and the like.
The processor 201 may be configured to call program instructions stored in the memory 205 and cause the modulation recognition apparatus 20 based on phase difference constellation clustering to perform the following operations:
carrying out symbol rate estimation, matched filtering, timing error estimation and difference filtering on a received signal to obtain a corresponding complex baseband signal;
performing adjacent sampling point subtraction on the complex baseband signal to realize phase difference;
performing clustering feature extraction on the constellation diagram corresponding to the sampling points after the phase difference;
and identifying signal modulation according to the result of the cluster feature extraction.
In some embodiments, the apparatus 20, when performing symbol rate estimation, matched filtering, timing error estimation and difference filtering on the received signal to obtain a corresponding complex baseband signal, is specifically configured to:
carrying out FFT calculation on the envelope of the received signal to obtain an envelope spectrum, and estimating a symbol rate based on a peak value in the envelope spectrum;
performing matched filtering on the received signal to obtain a maximum output signal-to-noise ratio signal;
estimating a timing error of a received signal by adopting an average estimation algorithm of non-data-assisted NDA;
and carrying out interpolation operation on the estimated timing error and the non-optimal sampling point obtained by sampling based on a cubic interpolation filter.
In some embodiments, the apparatus 20, when performing FFT computation on the envelope of the received signal to obtain an envelope spectrum, and estimating a symbol rate based on a peak in the envelope spectrum, is specifically configured to:
performing a modulus on the received signal by adopting an envelope spectrum estimation algorithm, and performing FFT operation on the baseband signal subjected to the modulus to obtain a corresponding envelope spectrum;
the position of the envelope spectrum at the spectral line is extracted to obtain a symbol rate estimate, wherein the envelope spectrum has a spectral line that is significant at the symbol rate.
In some embodiments, the complex baseband signal is
Figure BDA0002600620500000091
Wherein the content of the first and second substances,
Figure BDA0002600620500000092
for modulating the phase, Δ ωcIs a normalized carrier frequency offset.
The absolute phases of the nth and n +1 th symbols are:
Figure BDA0002600620500000101
Figure BDA0002600620500000102
and is provided with
Figure BDA0002600620500000103
In some embodiments, the phase difference restores the constellation state x that the received signal should have1Comprises the following steps: x is the number of1(m)＝x*(N) · x (N-1), wherein N ═ 2,3.. N, m ═ N-1.
In the embodiment of the invention, modulation identification of the communication satellite is realized through symbol rate estimation, matched filtering, timing error estimation, interpolation filtering, phase difference, constellation feature extraction and classification, the algorithm complexity is reduced, and meanwhile, the algorithm is suitable for multiple modulations, does not need to receive signals, is accurate and synchronous and has high identification accuracy.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
The above disclosure is only for the purpose of illustrating the preferred embodiments of the present invention, and it is therefore to be understood that the invention is not limited by the scope of the appended claims.

Claims (10)

1. A modulation identification method based on phase difference constellation diagram clustering is characterized by comprising the following steps:
carrying out symbol rate estimation, matched filtering, timing error estimation and difference filtering on a received signal to obtain a corresponding complex baseband signal;
performing adjacent sampling point subtraction on the complex baseband signal to realize phase difference;
performing clustering feature extraction on the constellation diagram corresponding to the sampling points after the phase difference;
and identifying signal modulation according to the result of the cluster feature extraction.
2. The method of claim 1, wherein the performing symbol rate estimation, matched filtering, timing error estimation and difference filtering on the received signal to obtain a corresponding complex baseband signal comprises:
carrying out FFT calculation on the envelope of a received signal to obtain an envelope spectrum, and estimating a symbol rate based on a peak value in the envelope spectrum;
performing matched filtering on the received signal to obtain a maximum output signal-to-noise ratio signal;
estimating the timing error of the received signal by adopting an average estimation algorithm of non-data-assisted NDA;
and carrying out interpolation operation on the estimated timing error and the non-optimal sampling point obtained by sampling based on a cubic interpolation filter.
3. The method of claim 2, wherein the FFT computation of the envelope of the received signal yields an envelope spectrum, and wherein estimating the symbol rate based on peaks in the envelope spectrum comprises:
performing a modulus on the received signal by adopting an envelope spectrum estimation algorithm, and performing FFT operation on the baseband signal subjected to the modulus to obtain a corresponding envelope spectrum;
and extracting the positions of the envelope spectrums at the spectral lines to obtain a symbol rate estimated value, wherein the envelope spectrums have obvious spectral lines at the symbol rate.
4. The method of claim 1,
the complex baseband signal is
Figure FDA0002600620490000011
Wherein the content of the first and second substances,
Figure FDA0002600620490000012
for modulating the phase, Δ ωcFor normalizing the carrier frequency offset, the absolute phases of the nth and n +1 th code elements are respectively:
Figure FDA0002600620490000013
and is provided with
Figure FDA0002600620490000014
5. The method of claim 4,
recovering the constellation diagram state x of the received signal after phase difference1Comprises the following steps: x is the number of1(m)＝x*(N) · x (N-1), wherein N ═ 2,3.. N, m ═ N-1.
6. A modulation identification device based on phase difference constellation diagram clustering is characterized by comprising:
the received signal processing module is used for carrying out symbol rate estimation, matched filtering, timing error estimation and difference filtering on the received signal to obtain a corresponding complex baseband signal;
the phase difference realization module is used for subtracting adjacent sampling points of the complex baseband signal to realize phase difference;
the clustering feature extraction module is used for extracting clustering features of the constellation diagram corresponding to the sampling points after the phase difference;
and the signal modulation identification module is used for identifying signal modulation according to the result of the cluster feature extraction.
7. The apparatus of claim 6, wherein the received signal processing module comprises:
a symbol rate estimation unit, configured to perform FFT computation on an envelope of a received signal to obtain an envelope spectrum, and estimate a symbol rate based on a peak in the envelope spectrum;
the matched filtering unit is used for performing matched filtering on the received signal to obtain a maximum output signal-to-noise ratio signal;
a timing error estimation unit for estimating a timing error of the received signal using an average estimation algorithm of non-data-assisted NDA;
and the difference filtering unit is used for carrying out interpolation operation on the estimated timing error and the non-optimal sampling point obtained by sampling based on the cubic interpolation filter.
8. The apparatus of claim 7, wherein the symbol rate estimation unit comprises:
the envelope spectrum calculating subunit is used for performing modulo calculation on the received signal by adopting an envelope spectrum estimation algorithm, and then performing FFT operation on the baseband signal subjected to the modulo calculation to obtain a corresponding envelope spectrum;
and the symbol rate estimation subunit is used for extracting the position of the envelope spectrum at the spectral line to obtain a symbol rate estimation value, wherein the envelope spectrum has an obvious spectral line at the symbol rate.
9. The apparatus of claim 6,
the complex baseband signal is
Figure FDA0002600620490000021
Wherein the content of the first and second substances,
Figure FDA0002600620490000022
for modulating the phase, Δ ωcFor normalizing the carrier frequency offset, the absolute phases of the nth and n +1 th code elements are respectively:
Figure FDA0002600620490000023
and is provided with
Figure FDA0002600620490000024
10. The apparatus of claim 9,
recovering the constellation diagram state x of the received signal after phase difference1Comprises the following steps: x is the number of1(m)＝x*(N) · x (N-1), wherein N ═ 2,3.. N, m ═ N-1.
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